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Understanding heavy tails of flood peak distributions

  • Statistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system. We then discuss to which extent the current knowledge supports or contradicts these hypotheses. We also discuss the statisticalStatistical distributions of flood peak discharge often show heavy tail behavior, that is, extreme floods are more likely to occur than would be predicted by commonly used distributions that have exponential asymptotic behavior. This heavy tail behavior may surprise flood managers and citizens, as human intuition tends to expect light tail behavior, and the heaviness of the tails is very difficult to predict, which may lead to unnecessarily high flood damage. Despite its high importance, the literature on the heavy tail behavior of flood distributions is rather fragmented. In this review, we provide a coherent overview of the processes causing heavy flood tails and the implications for science and practice. Specifically, we propose nine hypotheses on the mechanisms causing heavy tails in flood peak distributions related to processes in the atmosphere, the catchment, and the river system. We then discuss to which extent the current knowledge supports or contradicts these hypotheses. We also discuss the statistical conditions for the emergence of heavy tail behavior based on derived distribution theory and relate them to the hypotheses and flood generation mechanisms. We review the degree to which the heaviness of the tails can be predicted from process knowledge and data. Finally, we recommend further research toward testing the hypotheses and improving the prediction of heavy tails.show moreshow less

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Author details:Bruno MerzORCiDGND, Stefano Basso, Svenja Fischer, David Lun, Guenter Bloeschl, Ralf MerzORCiDGND, Bjorn Guse, Alberto ViglioneORCiD, Sergiy VorogushynORCiDGND, Elena MacdonaldORCiDGND, Luzie WietzkeORCiD, Andreas Schumann
DOI:https://doi.org/10.1029/2021WR030506
ISSN:0043-1397
ISSN:1944-7973
Title of parent work (English):Water resources research
Publisher:American Geophysical Union
Place of publishing:Washington
Publication type:Article
Language:English
Date of first publication:2022/06/15
Publication year:2022
Release date:2024/06/10
Tag:extreme events; flood frequency; flood risk; upper tail
Volume:58
Issue:6
Article number:e2021WR030506
Number of pages:37
Funding institution:German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) [FOR; 2416, 421,396,820]; Austrian Science Funds (FWF) "SPATE" project [I; 3174]; Projekt DEAL
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
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